Results for ' natural languages'

999 found
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  1.  51
    Are natural languages universal?Robert L. Martin - 1976 - Synthese 32 (3-4):271 - 291.
    We began by distinguishing Tarskian and Fitchean notions of universality in such a way that the claim that no language is universal in the sense of Tarski is compatible with accepting Fitchean universality. Then we examined a proposal involving two truth concepts — one that fit the Fitchean notion and another that followed Tarski's views on truth — finding little advantage in such generosity. We attempted a reformulation of Herzberger's argument for the negative view — the view that no language (...)
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  2. Ontology, natural language, and information systems: Implications of cross-linguistic studies of geographic terms.David M. Mark, Werner Kuhn, Barry Smith & A. G. Turk - 2003 - In Mark David M., Werner Kuhn, Smith Barry & Turk A. G. (eds.), 6th Annual Conference of the Association of Geographic Information Laboratories for Europe (AGILE),. pp. 45-50.
    Ontology has been proposed as a solution to the 'Tower of Babel' problem that threatens the semantic interoperability of information systems constructed independently for the same domain. In information systems research and applications, ontologies are often implemented by formalizing the meanings of words from natural languages. However, words in different natural languages sometimes subdivide the same domain of reality in terms of different conceptual categories. If the words and their associated concepts in two natural (...), or even in two terminological traditions within the same language, do not have common referents in the real world, an ontology based on word meanings will inherit the 'Tower of Babel' problem from the languages involved, rather than solve it. In this paper we present evidence from a preliminary comparison of landscape terms in English with those in the Yindjibarndi language of northwestern Australia demonstrating that this problem is not just hypothetical. Some possible solutions are suggested. (shrink)
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  3. Natural Language Ontology.Friederike Moltmann - 2017 - Oxford Encyclopedia of Linguistics.
    The aim of natural language ontology is to uncover the ontological categories and structures that are implicit in the use of natural language, that is, that a speaker accepts when using a language. This article aims to clarify what exactly the subject matter of natural language ontology is, what sorts of linguistic data it should take into account, how natural language ontology relates to other branches of metaphysics, in what ways natural language ontology is important, (...)
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  4. Natural language and natural selection.Steven Pinker & Paul Bloom - 1990 - Behavioral and Brain Sciences 13 (4):707-27.
    Many people have argued that the evolution of the human language faculty cannot be explained by Darwinian natural selection. Chomsky and Gould have suggested that language may have evolved as the by-product of selection for other abilities or as a consequence of as-yet unknown laws of growth and form. Others have argued that a biological specialization for grammar is incompatible with every tenet of Darwinian theory – that it shows no genetic variation, could not exist in any intermediate forms, (...)
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  5.  83
    Natural Language Understanding.James Allen - 1995 - Benjamin Cummings.
    From a leading authority in artificial intelligence, this book delivers a synthesis of the major modern techniques and the most current research in natural language processing. The approach is unique in its coverage of semantic interpretation and discourse alongside the foundational material in syntactic processing.
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  6. Situations in natural language semantics.Angelika Kratzer - 2008 - Stanford Encyclopedia of Philosophy.
    Situation semantics was developed as an alternative to possible worlds semantics. In situation semantics, linguistic expressions are evaluated with respect to partial, rather than complete, worlds. There is no consensus about what situations are, just as there is no consensus about what possible worlds or events are. According to some, situations are structured entities consisting of relations and individuals standing in those relations. According to others, situations are particulars. In spite of unresolved foundational issues, the partiality provided by situation semantics (...)
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  7. Natural Language and its Ontology.Friederike Moltmann - 2019 - In Alvin Goldman & Brian Mclaughlin (eds.), Metaphysics and Cognitive Science. Oxford: Oxford University Press. pp. 206-232.
    This paper gives a characterization of the ontology implicit in natural language and the entities it involves, situates natural language ontology within metaphysics, and responds to Chomskys' dismissal of externalist semantics.
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  8. New Foundations (Natural Language as a Complex System, or New Foundations for Philosophical Semantics, Epistemology and Metaphysics, Based on the Process-Socio-Environmental Conception of Linguistic Meaning and Knowledge).Gustavo Picazo - 2021 - Journal of Research in Humanities and Social Science 9 (6):33–44.
    In this article, I explore the consequences of two commonsensical premises in semantics and epistemology: (1) natural language is a complex system rooted in the communal life of human beings within a given environment; and (2) linguistic knowledge is essentially dependent on natural language. These premises lead me to emphasize the process-socio-environmental character of linguistic meaning and knowledge, from which I proceed to analyse a number of long-standing philosophical problems, attempting to throw new light upon them on these (...)
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  9.  94
    Logic & Natural Language: On Plural Reference and its Semantic and Logical Significance.Hanoch Ben-Yami - 2004 - Routledge.
    Frege's invention of the predicate calculus has been the most influential event in the history of modern logic. The calculus’ place in logic is so central that many philosophers think, in fact, of it when they think of logic. This book challenges the position in contemporary logic and philosophy of language of the predicate calculus claiming that it is based on mistaken assumptions. Ben-Yami shows that the predicate calculus is different from natural language in its fundamental semantic charac.
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  10.  89
    Natural Language Inference in Coq.Stergios Chatzikyriakidis & Zhaohui Luo - 2014 - Journal of Logic, Language and Information 23 (4):441-480.
    In this paper we propose a way to deal with natural language inference by implementing Modern Type Theoretical Semantics in the proof assistant Coq. The paper is a first attempt to deal with NLI and natural language reasoning in general by using the proof assistant technology. Valid NLIs are treated as theorems and as such the adequacy of our account is tested by trying to prove them. We use Luo’s Modern Type Theory with coercive subtyping as the formal (...)
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  11. Natural Language Understanding: Methodological Conceptualization.Vitalii Shymko - 2019 - Psycholinguistics 25 (1):431-443.
    This article contains the results of a theoretical analysis of the phenomenon of natural language understanding (NLU), as a methodological problem. The combination of structural-ontological and informational-psychological approaches provided an opportunity to describe the subject matter field of NLU, as a composite function of the mind, which systemically combines the verbal and discursive structural layers. In particular, the idea of NLU is presented, on the one hand, as the relation between the discourse of a specific speech message and the (...)
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  12.  15
    Natural Language and Possible Minds: How Language Uncovers the Cognitive Landscape of Nature.Prakash Mondal - 2017 - Boston: Brill | Rodopi.
    _Natural Language and Possible Minds: How Language Uncovers the Cognitive Landscape of Nature_ examines the intrinsic connection between natural language and the nature of mentality, offering to show how language can shed light on the forms of other types of mentality in non-humans.
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  13.  42
    Natural Language and Logic of Agency.Johan van Benthem - 2014 - Journal of Logic, Language and Information 23 (3):367-382.
    This light piece reflects on analogies between two often disjoint streams of research: the logical semantics and pragmatics of natural language and dynamic logics of general information-driven agency. The two areas show significant overlap in themes and tools, and yet, the focus seems subtly different in each, defying a simple comparison. We discuss some unusual questions that emerge when the two are put side by side, without any pretense at covering the whole literature or at reaching definitive conclusions.
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  14.  13
    Representing Time in Natural Language: The Dynamic Interpretation of Tense and Aspect.Alice G. B. Ter Meulen - 1997 - MIT Press.
    The topic of temporal meaning in texts has received considerable attention in recent years from scholars in linguistics, logical semantics, cognitive science, and artificial intelligence. Representing Time in Natural Language offers a systematic and detailed account of how we use temporal information contained in a text or in discourse to reason about the flow of time, inferring the order in which events happened when this is not explicitly stated. A new representational system is designed to formalize an appropriately context-dependent (...)
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  15. Natural Language Processing and Semantic Network Visualization for Philosophers.Mark Alfano & Andrew Higgins - 2019 - In Eugen Fischer & Mark Curtis (eds.), Methodological Advances in Experimental Philosophy. London: Bloomsbury Press.
    Progress in philosophy is difficult to achieve because our methods are evidentially and rhetorically weak. In the last two decades, experimental philosophers have begun to employ the methods of the social sciences to address philosophical questions. However, the adequacy of these methods has been called into question by repeated failures of replication. Experimental philosophers need to incorporate more robust methods to achieve a multi-modal perspective. In this chapter, we describe and showcase cutting-edge methods for data-mining and visualization. Big data is (...)
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  16.  1
    Natural language syntax complies with the free-energy principle.Elliot Murphy, Emma Holmes & Karl Friston - 2024 - Synthese 203 (5):1-35.
    Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design—such as “minimal search” criteria from theoretical (...)
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  17. Natural Language Ontology (Routledge Handbook of Metametaphysics).Friederike Moltmann - 2020 - In Ricki Bliss & James Miller (eds.), The Routledge Handbook of Metametaphysics. New York, NY: Routledge. pp. 325-338.
    This paper gives an outline of natural language ontology as a subdiscipline of both linguistics and philosophy. It argues that part of the constructional ontology reflected in natural language is in significant respects on a par with syntax (on the generative view).
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  18.  13
    Natural language associability in paired-associate learning.Clinton B. Walker, William E. Montague & Alexander J. Wearing - 1970 - Journal of Experimental Psychology 84 (2):264.
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  19. Logical Consequence and Natural Language.Michael Glanzberg - 2015 - In Colin R. Caret & Ole T. Hjortland (eds.), Foundations of Logical Consequence. Oxford University Press. pp. 71-120.
    One of the great successes in the study of language has been the application of formal methods, including those of formal logic. Even so, this chapter argues against one way of accounting for this success, by arguing that the study of natural language semantics and of logical consequence relations are not the same. There is indeed a lot we can glean about logic from looking at our languages, and at our inferential practices, but the semantic properties of (...) languages do not determine genuine logical consequence relations. We can get from natural language semantics to logical consequence, but only by a significant process of identification of logical constants, abstraction, and idealization. The chapter also discusses different approaches to the nature of logical consequence, and examines which allow logic and natural language to come closer together. (shrink)
     
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  20. Natural-Language Content: A Proof-Theoretic Perspective.Dov Gabbay & Ruth Kempson - 1992 - In Proceedings of the Eigth Amsterdam Formal Semantics Colloqium. University of Amsterdam.
     
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  21. Natural language and virtual belief.Keith Frankish - 1998 - In Peter Carruthers & Jill Boucher (eds.), Language and Thought: Interdisciplinary Themes. Cambridge University Press. pp. 248.
    This chapter outlines a new argument for the view that language has a cognitive role. I suggest that humans exhibit two distinct kinds of belief state, one passively formed, the other actively formed. I argue that actively formed beliefs (_virtual beliefs_, as I call them) can be identified with _premising policies_, and that forming them typically involves certain linguistic operations. I conclude that natural language has at least a limited cognitive role in the formation and manipulation of virtual beliefs.
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  22.  26
    Natural Language Grammar Induction using a Constituent-Context Model.Dan Klein & Christopher D. Manning - unknown
    This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according to generative PCFG models. In contrast, we employ a simpler probabilistic model over trees based directly on constituent identity and linear context, and use an EM-like iterative procedure to induce structure. This method produces much higher quality analyses, giving the best published results on the ATIS dataset.
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  23.  44
    Natural language understanding within a cognitive semantics framework.Inger Lytje - 1989 - AI and Society 4 (4):276-290.
    The article argues that cognitive linguistic theory may prove an alternative to the Montague paradigm for designing natural language understanding systems. Within this framework it describes a system which models language understanding as a dialogical process between user and computer. The system operates with natural language texts as input and represent language meaning as entity-relationship diagrams.
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  24.  67
    Natural language processing for transparent communication between public administration and citizens.Bernardo Magnini, Elena Not, Oliviero Stock & Carlo Strapparava - 2000 - Artificial Intelligence and Law 8 (1):1-34.
    This paper presents two projects concerned with the application of natural language processing technology for improving communication between Public Administration and citizens. The first project, GIST,is concerned with automatic multilingual generation of instructional texts for form-filling. The second project, TAMIC, aims at providing an interface for interactive access to information, centered on natural language processing and supposed to be used by the clerk but with the active participation of the citizen.
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  25.  94
    Natural language, sortal reducibility and generalized quantifiers.Edward L. Keenan - 1993 - Journal of Symbolic Logic 58 (1):314-325.
    Recent work in natural language semantics leads to some new observations on generalized quantifiers. In § 1 we show that English quantifiers of type $ $ are booleanly generated by their generalized universal and generalized existential members. These two classes also constitute the sortally reducible members of this type. Section 2 presents our main result--the Generalized Prefix Theorem (GPT). This theorem characterizes the conditions under which formulas of the form Q1x 1⋯ Qnx nRx 1⋯ xn and q1x 1⋯ qnx (...)
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  26.  99
    Natural language processing using a propositional semantic network with structured variables.Syed S. Ali & Stuart C. Shapiro - 1993 - Minds and Machines 3 (4):421-451.
    We describe a knowledge representation and inference formalism, based on an intensional propositional semantic network, in which variables are structures terms consisting of quantifier, type, and other information. This has three important consequences for natural language processing. First, this leads to an extended, more natural formalism whose use and representations are consistent with the use of variables in natural language in two ways: the structure of representations mirrors the structure of the language and allows re-use phenomena such (...)
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  27. Natural languages as collections of resources.Robin Cooper & Aarne Ranta - unknown
    We propose a shift in perspective from the view of natural languages as formal languages to natural languages as a collection of resources for constructing local languages for use in particular situations. This is suggested by our experience constructing natural language grammars for particular applications using the Grammatical Framework. It points to a research programme investigating how such resources play a role in linguistic innovation by agents constructing situation-specific local languages and how (...)
     
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  28.  24
    Natural language semantics: formation and valuation.Brendan S. Gillon - 2019 - Cambridge, Massachussetts: The MIT Press.
    This textbook, which is completely self-contained and can be read by anyone with a secondary school education, is the result of the author's material prepared over the past 15 years of teaching introductory natural language semantics to graduate and undergraduate students at McGill University. The intended audience comprises undergraduate and graduate students in linguistics as well as those in philosophy, computer science and psychology with an interest in natural language semantics. The aim of the textbook is to teach (...)
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  29.  33
    Natural language generation of biomedical argumentation for lay audiences.Nancy Green, Rachael Dwight, Kanyamas Navoraphan & Brian Stadler - 2011 - Argument and Computation 2 (1):23 - 50.
    This article presents an architecture for natural language generation of biomedical argumentation. The goal is to reconstruct the normative arguments that a domain expert would provide, in a manner that is transparent to a lay audience. Transparency means that an argument's structure and functional components are accessible to its audience. Transparency is necessary before an audience can fully comprehend, evaluate or challenge an argument, or re-evaluate it in light of new findings about the case or changes in scientific knowledge. (...)
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  30. Natural languages and context-free languages.Geoffrey K. Pullum & Gerald Gazdar - 1980 - Linguistics and Philosophy 4 (4):471 - 504.
    Notice that this paper has not claimed that all natural languages are CFL's. What it has shown is that every published argument purporting to demonstrate the non-context-freeness of some natural language is invalid, either formally or empirically or both.18 Whether non-context-free characteristics can be found in the stringset of some natural language remains an open question, just as it was a quarter century ago.Whether the question is ultimately answered in the negative or the affirmative, there will (...)
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  31. Understanding Natural Language.T. Winograd - 1974 - British Journal for the Philosophy of Science 25 (1):85-88.
  32. Ethical pitfalls for natural language processing in psychology.Mark Alfano, Emily Sullivan & Amir Ebrahimi Fard - forthcoming - In Morteza Dehghani & Ryan Boyd (eds.), The Atlas of Language Analysis in Psychology. Guilford Press.
    Knowledge is power. Knowledge about human psychology is increasingly being produced using natural language processing (NLP) and related techniques. The power that accompanies and harnesses this knowledge should be subject to ethical controls and oversight. In this chapter, we address the ethical pitfalls that are likely to be encountered in the context of such research. These pitfalls occur at various stages of the NLP pipeline, including data acquisition, enrichment, analysis, storage, and sharing. We also address secondary uses of the (...)
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  33.  7
    Bayesian Natural Language Semantics and Pragmatics.Henk Zeevat & Hans-Christian Schmitz (eds.) - 2015 - Springer.
    The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics (...)
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  34.  48
    The semantic representation of natural language.Michael Levison - 2012 - New York: Bloomsbury Academic.
    Introduction -- Basic concepts -- Previous approaches -- Semantic expressions: introduction -- Formal issues -- Semantic expressions: basic features -- Advanced features -- Applications: capture -- Three little pigs -- Applications: creation.
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  35. Levels of Ontology and Natural Language: the Case of the Ontology of Parts and Wholes.Friederike Moltmann - 2021 - In James Miller (ed.), The Language of Ontology. Oxford: Oxford University Press.
    It is common in contemporary metaphysics to distinguish two levels of ontology: the ontology of ordinary objects and the ontology of fundamental reality. This papers argues that natural language reflects not only the ontology of ordinary objects, but also a language-driven ontology, which is involved in the mass-count distinction and part-structure-sensitive semantic selection, as well as perhaps the light ontology of pleonastic entities. The paper recasts my older theory of situated part structures without situations, making use of a primitive (...)
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  36.  33
    Natural language interfaces and strategic computing.Geoffrey K. Pullum - 1987 - AI and Society 1 (1):47-58.
    Modern weaponry is often too complex for unaided human operation, and is largely or totally controlled by computers. But modern software, particularly artificial intelligence software, exhibits such complexity and inscrutability that there are grave dangers associated with its use in non-benign applications. Recent efforts to make computer systems more accessible to military personnel through natural language processing systems, as proposed in the Strategic Computing Initiative of the Defense Advanced Research Projects Agency, increases rather than decreases the dangers of unpredictable (...)
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  37.  27
    Continuations and Natural Language.Chris Barker & Chung-Chieh Shan - 2014 - Oxford University Press.
    This book takes concepts developed by researchers in theoretical computer science and adapts and applies them to the study of natural language meaning. Summarizing over a decade of research, Chris Barker and Chung-chieh Shan put forward the Continuation Hypothesis: that the meaning of a natural language expression can depend on its own continuation.
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  38. Generalized quantifiers in natural language semantics.Dag Westerstêahl - 1996 - In Shalom Lappin & Chris Fox (eds.), Handbook of Contemporary Semantic Theory. Hoboken: Wiley-Blackwell.
  39.  17
    Natural language processing for legal document review: categorising deontic modalities in contracts.S. Georgette Graham, Hamidreza Soltani & Olufemi Isiaq - forthcoming - Artificial Intelligence and Law:1-22.
    The contract review process can be a costly and time-consuming task for lawyers and clients alike, requiring significant effort to identify and evaluate the legal implications of individual clauses. To address this challenge, we propose the use of natural language processing techniques, specifically text classification based on deontic tags, to streamline the process. Our research question is whether natural language processing techniques, specifically dense vector embeddings, can help semi-automate the contract review process and reduce time and costs for (...)
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  40. Natural language and thought: Thinking in English.Barbara Abbott - 1995 - Behavior and Philosophy 23 (2):49-55.
  41.  30
    Processing natural language arguments with the platform.Patrick Saint-Dizier - 2012 - Argument and Computation 3 (1):49 - 82.
    In this article, we first present the platform and the Dislog language, designed for discourse analysis with a logic and linguistic perspective. The platform has now reached a certain level of maturity which allows the recognition of a large diversity of discourse structures including general-purpose rhetorical structures as well as domain-specific discourse structures. The Dislog language is based on linguistic considerations and includes knowledge access and inference capabilities. Functionalities of the language are presented together with a method for writing discourse (...)
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  42. Natural language generation in healthcare.Alison Cawsey - unknown
    Good communication is vital in healthcare both among healthcare professionals and be tween healthcare professionals and their patients And well written documents describing and or explaining the information in structured databases may be easier to comprehend more edifying and even more convincing than the structured data even when presented in tabu lar or graphic form Documents may be automatically generated from structured data using techniques from the eld of natural language generation These techniques are concerned with how the content (...)
     
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  43. Reference to numbers in natural language.Friederike Moltmann - 2013 - Philosophical Studies 162 (3):499 - 536.
    A common view is that natural language treats numbers as abstract objects, with expressions like the number of planets, eight, as well as the number eight acting as referential terms referring to numbers. In this paper I will argue that this view about reference to numbers in natural language is fundamentally mistaken. A more thorough look at natural language reveals a very different view of the ontological status of natural numbers. On this view, numbers are not (...)
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  44. Idealisation in Natural Language Semantics: Truth-Conditions for Radical Contextualists.Gabe Dupre - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of (...) language meaning. From this perspective, disparity between the scientific model and its real-world target is to be expected. I elaborate on what such an approach to semantics would look like. (shrink)
     
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  45.  25
    Natural Language Semantics and Guise Theory.Francesco Orilia - 1986 - Dissertation, Indiana University
    I assume that the task of natural language semantics is to provide an unambiguous logical language into which natural language can be translated in such a way that the translating expressions display a structure which is isomorphic to the meaning of the translated expressions. Since language is a means of thinking and communicating mental contents, the meanings of singular terms cannot be the individuals of the substratist tradition, because such individuals are not cognizable entities. Thus I propose that (...)
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  46.  11
    Gradability in Natural Language: Logical and Grammatical Foundations.Heather Burnett - 2016 - Oxford University Press UK.
    This book presents a new theory of the relationship between vagueness, context-sensitivity, gradability, and scale structure in natural language. Heather Burnett argues that it is possible to distinguish between particular subclasses of adjectival predicatesDLrelative adjectives like tall, total adjectives like dry, partial adjectives like wet, and non-scalar adjectives like hexagonalDLon the basis of how their criteria of application vary depending on the context; how they display the characteristic properties of vague language; and what the properties of their associated orders (...)
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  47.  85
    Natural selection and natural language.Steven Pinker & Paul Bloom - 1990 - Behavioral and Brain Sciences 13 (4):707-784.
    Many people have argued that the evolution of the human language faculty cannot be explained by Darwinian natural selection. Chomsky and Gould have suggested that language may have evolved as the by-product of selection for other abilities or as a consequence of as-yet unknown laws of growth and form. Others have argued that a biological specialization for grammar is incompatible with every tenet of Darwinian theory – that it shows no genetic variation, could not exist in any intermediate forms, (...)
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  48.  14
    Natural Language Dialog with a Tutor System for Mathematical Proofs.Christoph Benzmüller, Helmut Horacek, Ivana Kruijff-Korbayova, Manfred Pinkal, Jörg Siekmann & Magdalena Wolska - 2007 - In Ruqian Lu, Jörg Siekmann & Carsten Ullrich (eds.), Cognitive Systems: Joint Chinese-German Workshop, Shanghai, China, March 7-11, 2005, Revised Selected Papers. Springer. pp. 1-14.
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  49. Indefinite Extensibility in Natural Language.Laureano Luna - 2013 - The Monist 96 (2):295-308.
    The Monist’s call for papers for this issue ended: “if formalism is true, then it must be possible in principle to mechanize meaning in a conscious thinking and language-using machine; if intentionalism is true, no such project is intelligible”. We use the Grelling-Nelson paradox to show that natural language is indefinitely extensible, which has two important consequences: it cannot be formalized and model theoretic semantics, standard for formal languages, is not suitable for it. We also point out that (...)
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  50. Understanding natural language.John Haugeland - 1979 - Journal of Philosophy 76 (November):619-32.
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